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Supervisory control of mobile sensor networks: math formulation, simulation, and implementation.

Vincenzo Giordano1, Prasanna Ballal, Frank Lewis

  • 1Dipartimento di Elettrotecnica ed Elettronica, Politecnico di Bari, Italy. giordano@deemail.poliba.it

IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society
|August 15, 2006
PubMed
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This study introduces a novel discrete-event controller (DEC) for coordinating wireless sensor networks (WSNs) with ground sensors and robots. The DEC enhances adaptability and efficiency in dynamic WSN environments.

Area of Science:

  • Robotics
  • Computer Science
  • Network Engineering

Background:

  • Wireless Sensor Networks (WSNs) present unique supervisory control challenges due to their dynamic nature.
  • Coordinating heterogeneous agents like unattended ground sensors (UGSs) and mobile sensor robots requires sophisticated control mechanisms.
  • Existing control methods may struggle with the adaptability needed for changing missions and unpredictable node failures in WSNs.

Purpose of the Study:

  • To develop and evaluate a novel discrete-event controller (DEC) for the effective coordination of cooperating heterogeneous WSNs.
  • To introduce new tools for DEC design and operation, enhancing its applicability in dynamic WSN environments.
  • To demonstrate the DEC's capability in task sequencing, resource allocation, and dynamic priority assignment.

Main Methods:

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  • Utilized a matrix formulation for the DEC to manage missions, agent additions, and failures.
  • Developed methods for generating and modifying supervisory matrices based on mission planning and network events.
  • Implemented a novel dynamic priority assignment weighting approach for sensor selection.
  • Designed and implemented the DEC on an experimental WSN prototyping system.

Main Results:

  • The DEC effectively sequences tasks and assigns sensor resources based on environmental perception.
  • The matrix formulation provides a robust framework for adaptable WSN control.
  • New tools facilitate dynamic matrix modification for handling node failures or additions.
  • The dynamic priority weighting ensures optimal sensor utilization for mission tasks.
  • Simulation and experimental results validate the effectiveness and versatility of the DEC architecture.

Conclusions:

  • The developed DEC offers a complete dynamical description of WSN systems, enabling fast programming and efficient implementation.
  • The control architecture demonstrates significant effectiveness and versatility in coordinating heterogeneous WSNs.
  • The DEC provides a powerful solution for supervisory control in complex and dynamic WSN applications.